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Assessing wastewater-based epidemiology for the prediction of SARS-CoV-2 incidence in Catalonia

While wastewater-based epidemiology has proven a useful tool for epidemiological surveillance during the COVID-19 pandemic, few quantitative models comparing virus concentrations in wastewater samples and cumulative incidence have been established. In this work, a simple mathematical model relating...

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Detalles Bibliográficos
Autores principales: Joseph-Duran, Bernat, Serra-Compte, Albert, Sàrrias, Miquel, Gonzalez, Susana, López, Daniel, Prats, Clara, Català, Martí, Alvarez-Lacalle, Enric, Alonso, Sergio, Arnaldos, Marina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9443647/
https://www.ncbi.nlm.nih.gov/pubmed/36064874
http://dx.doi.org/10.1038/s41598-022-18518-9
Descripción
Sumario:While wastewater-based epidemiology has proven a useful tool for epidemiological surveillance during the COVID-19 pandemic, few quantitative models comparing virus concentrations in wastewater samples and cumulative incidence have been established. In this work, a simple mathematical model relating virus concentration and cumulative incidence for full contagion waves was developed. The model was then used for short-term forecasting and compared to a local linear model. Both scenarios were tested using a dataset composed of samples from 32 wastewater treatment plants and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) incidence data covering the corresponding geographical areas during a 7-month period, including two contagion waves. A population-averaged dataset was also developed to model and predict the incidence over the full geography. Overall, the mathematical model based on wastewater data showed a good correlation with cumulative cases and allowed us to anticipate SARS-CoV-2 incidence in one week, which is of special relevance in situations where the epidemiological monitoring system cannot be fully implemented.